AIMC Topic: Peptides

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Intelligent decoding platform for peptide sequences: SERS detection via high affinity self-assembled silver nanoparticles and machine learning analysis.

Analytica chimica acta
BACKGROUND: Peptides are compounds formed by the dehydration-condensation reaction of two or more amino acids which play an important role in the life functions of the organism. Changes in the structure of amino acids and peptides are vital for eluci...

Advances of deep Neural Networks (DNNs) in the development of peptide drugs.

Future medicinal chemistry
Peptides are able to bind to difficult disease targets with high potency and specificity, providing great opportunities to meet unmet medical requirements. Nevertheless, the unique features of peptides, such as their small size, high structural flexi...

Enhanced authentication of organic milk using MALDI-TOF MS with combined lipid-peptide fingerprinting and machine learning integration.

Food chemistry
This study introduces a method for authenticating organic milk and determining its geographic region using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Both lipids and peptides were analyzed, and their ...

Deep Learning Combined with Quantitative Structure‒Activity Relationship Accelerates De Novo Design of Antifungal Peptides.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Novel antifungal drugs that evade resistance are urgently needed for Candida infections. Antifungal peptides (AFPs) are potential candidates due to their specific mechanism of action, which makes them less prone to developing drug resistance. An AFP ...

Artificial-Intelligence Bio-Inspired Peptide for Salivary Detection of SARS-CoV-2 in Electrochemical Biosensor Integrated with Machine Learning Algorithms.

Biosensors
Developing affordable, rapid, and accurate biosensors is essential for SARS-CoV-2 surveillance and early detection. We created a bio-inspired peptide, using the SAGAPEP AI platform, for COVID-19 salivary diagnostics via a portable electrochemical dev...

Deep Learning Predicts Non-Normal Transmission Distributions in High-Field Asymmetric Waveform Ion Mobility (FAIMS) Directly from Peptide Sequence.

Analytical chemistry
Peptide ion mobility adds an extra dimension of separation to mass spectrometry-based proteomics. The ability to accurately predict peptide ion mobility would be useful to expedite assay development and to discriminate true answers in a database sear...

Feature selection enhances peptide binding predictions for TCR-specific interactions.

Frontiers in immunology
INTRODUCTION: T-cell receptors (TCRs) play a critical role in the immune response by recognizing specific ligand peptides presented by major histocompatibility complex (MHC) molecules. Accurate prediction of peptide binding to TCRs is essential for a...

PeptideForest: Semisupervised Machine Learning Integrating Multiple Search Engines for Peptide Identification.

Journal of proteome research
The first step in bottom-up proteomics is the assignment of measured fragmentation mass spectra to peptide sequences, also known as peptide spectrum matches. In recent years novel algorithms have pushed the assignment to new heights; unfortunately, d...

Artificial intelligence in peptide-based drug design.

Drug discovery today
Protein-protein interactions (PPIs) are fundamental to a variety of biological processes, but targeting them with small molecules is challenging because of their large and complex interaction interfaces. However, peptides have emerged as highly promi...

From Sea Cucumbers to Soft Robots: A Photothermal-Responsive Hydrogel Actuator with Shape Memory.

ACS applied materials & interfaces
Soft robotics has undergone considerable progress driven by materials that can effectively transduce external stimuli into mechanical actuation. Here, we report the development of a photothermal-responsive hydrogel actuator with shape memory capabili...